Sort by
Refine Your Search
-
, and costs of running diverse applications in large-scale distributed systems. This project offers researchers and students a chance to explore cutting-edge concepts in AI-driven infrastructure
-
In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
-
paradigms rely on a fragile "closed-world" assumption: that the unlabeled pool perfectly reflects the distribution of the labelled seed set. In real-world deployments, this is rarely true. Data streams
-
hospital or population often fail when applied elsewhere due to distributional shifts. Since acquiring new labeled data is often costly or infeasible due to rare diseases, limited expert availability, and
-
missing modalities and distribution shift. Design uncertainty-aware decision frameworks for downstream tasks. Expected Contributions This PhD project is expected to contribute: Scalable Bayesian uncertainty
-
inside cold clouds of gas and dust, but these clouds are messy, complex, and difficult to observe in full. A lot of my work is about building and analysing better maps of this material so that we can
-
, from swarm robotics to mesh networks. The prototypical model system for the investigation of self-organised task allocation are social insect colonies, such as bees and ants. They are able to distribute
-
; Circular economy and waste-to-resource systems; Distributed and decentralised infrastructure systems; Adaptive planning pathways under multiple climate scenarios. The projects should aim to generate
-
strong out-of-distribution generalization capability [2]. If user-specific information is identified and removable from the input data, the devised techniques can also be applied for privacy-sensitive
-
privacy needs of patients as well as the limitations of mobile environments, there is a need for considering a multi-level federated learning architecture for the mobile-edge-cloud continuum. The project